Unmanned aerial vehicles in hydrology and water management: Applications, challenges and perspectives

Bharat Sharma Acharya*, Mahendra Bhandari, Filippo Bandini, Alonso Pizarro, Matthew Perks, Deepak Raj Joshi, Sheng Wang, Toby Dogwiler, Ram L Ray, Gehendra Kharel, Sadikshya Sharma

*Corresponding author for this work

    Research output: Contribution to journalReviewpeer-review

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    Abstract

    The hydrologic sciences and water resources management have long depended on a combination of in-situ measurements and remotely-sensed data for research and regulatory purposes. In-situ measurements are constrained in their spatial distribution by both logistics and costs. Satellite- and manned aircraft-based remote sensing provide spatially broad data, but often of a coarse resolution. Furthermore, all these data collection methods are often limited in their ability to respond to specific short-term events when the data and imagery could inform real-time assessment and decision-making, especially during and immediately after natural disasters. Researchers and regulators are increasingly using Unmanned Aerial Vehicles (UAVs) to fill these gaps in both spatial and temporal data resolution. UAVs are often more cost-effective than traditional remote sensing or in-situ data collection methodologies and the availability of new advancements in UAV design, power supply, payload capacity, and sensors has been driving rapid innovations in their use in the hydrological sciences. This in-depth review explores these UAV technologies and how they are being employed for on-demand and cost-effective characterization, monitoring, assessment, and modeling of soil and water resources. Our discussion addresses both key opportunities and challenges in surface water and groundwater studies, land-atmosphere interaction studies, water management in agriculture and forestry, ecosystem monitoring, and hydrological modeling.
    Original languageEnglish
    Article numbere2021WR029925
    JournalWater Resources Research
    Volume57
    Issue number11
    Number of pages33
    ISSN0043-1397
    DOIs
    Publication statusPublished - 2021

    Keywords

    • Environmental Monitoring
    • Hydrology
    • Hyperspectral Sensors
    • LiDAR
    • Modeling
    • Remote Sensing
    • Unmanned Aerial Vehicles

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